R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(1830
+ ,67.643
+ ,64.033
+ ,131.676
+ ,1831
+ ,69.371
+ ,65.679
+ ,135.050
+ ,1832
+ ,66.294
+ ,62.776
+ ,129.070
+ ,1833
+ ,70.768
+ ,67.024
+ ,137.792
+ ,1834
+ ,71.774
+ ,67.988
+ ,139.762
+ ,1835
+ ,73.388
+ ,69.529
+ ,142.917
+ ,1836
+ ,74.040
+ ,70.158
+ ,144.198
+ ,1837
+ ,73.238
+ ,69.410
+ ,142.648
+ ,1838
+ ,78.121
+ ,74.049
+ ,152.170
+ ,1839
+ ,69.825
+ ,66.197
+ ,136.022
+ ,1840
+ ,71.099
+ ,67.043
+ ,138.142
+ ,1841
+ ,70.676
+ ,67.459
+ ,138.135
+ ,1842
+ ,69.515
+ ,65.512
+ ,135.027
+ ,1843
+ ,68.246
+ ,64.665
+ ,132.911
+ ,1844
+ ,68.594
+ ,65.382
+ ,133.976
+ ,1845
+ ,70.405
+ ,66.607
+ ,137.012
+ ,1846
+ ,61.223
+ ,58.387
+ ,119.610
+ ,1847
+ ,60.542
+ ,57.564
+ ,118.106
+ ,1848
+ ,61.952
+ ,58.431
+ ,120.383
+ ,1849
+ ,68.173
+ ,65.012
+ ,133.185
+ ,1850
+ ,67.240
+ ,64.176
+ ,131.416
+ ,1851
+ ,68.739
+ ,65.509
+ ,134.248
+ ,1852
+ ,69.234
+ ,65.163
+ ,134.397
+ ,1853
+ ,65.570
+ ,62.158
+ ,127.728
+ ,1854
+ ,67.408
+ ,64.429
+ ,131.837
+ ,1855
+ ,64.630
+ ,61.325
+ ,125.955
+ ,1856
+ ,68.848
+ ,65.339
+ ,134.187
+ ,1857
+ ,73.370
+ ,69.921
+ ,143.291
+ ,1858
+ ,74.292
+ ,70.782
+ ,145.074
+ ,1859
+ ,76.525
+ ,73.287
+ ,149.812
+ ,1860
+ ,74.368
+ ,70.300
+ ,144.668
+ ,1861
+ ,75.674
+ ,71.579
+ ,147.253
+ ,1862
+ ,74.868
+ ,70.700
+ ,145.568
+ ,1863
+ ,79.824
+ ,75.740
+ ,155.564
+ ,1864
+ ,80.022
+ ,75.850
+ ,155.872
+ ,1865
+ ,79.942
+ ,76.381
+ ,156.323
+ ,1866
+ ,80.622
+ ,77.388
+ ,158.010
+ ,1867
+ ,80.079
+ ,75.519
+ ,155.598
+ ,1868
+ ,79.212
+ ,75.573
+ ,154.785
+ ,1869
+ ,80.626
+ ,76.668
+ ,157.294
+ ,1870
+ ,83.551
+ ,79.387
+ ,162.938
+ ,1871
+ ,80.407
+ ,76.876
+ ,157.283
+ ,1872
+ ,85.053
+ ,81.021
+ ,166.074
+ ,1873
+ ,86.399
+ ,82.883
+ ,169.282
+ ,1874
+ ,88.536
+ ,84.016
+ ,172.552
+ ,1875
+ ,89.008
+ ,85.047
+ ,174.055
+ ,1876
+ ,89.652
+ ,85.757
+ ,175.409
+ ,1877
+ ,88.904
+ ,84.792
+ ,173.696
+ ,1878
+ ,87.472
+ ,83.811
+ ,171.283
+ ,1879
+ ,88.631
+ ,84.691
+ ,173.322
+ ,1880
+ ,87.221
+ ,83.496
+ ,170.717
+ ,1881
+ ,88.759
+ ,85.470
+ ,174.229
+ ,1882
+ ,90.127
+ ,85.212
+ ,175.339
+ ,1883
+ ,88.709
+ ,84.802
+ ,173.511
+ ,1884
+ ,90.030
+ ,85.809
+ ,175.839
+ ,1885
+ ,88.697
+ ,85.119
+ ,173.816
+ ,1886
+ ,88.762
+ ,85.228
+ ,173.990
+ ,1887
+ ,89.475
+ ,85.302
+ ,174.777
+ ,1888
+ ,88.936
+ ,85.883
+ ,174.819
+ ,1889
+ ,90.411
+ ,86.315
+ ,176.726
+ ,1890
+ ,90.004
+ ,86.195
+ ,176.199
+ ,1891
+ ,92.725
+ ,88.227
+ ,180.952
+ ,1892
+ ,90.252
+ ,86.411
+ ,176.663
+ ,1893
+ ,93.226
+ ,89.120
+ ,182.346
+ ,1894
+ ,92.575
+ ,88.030
+ ,180.605
+ ,1895
+ ,93.125
+ ,89.372
+ ,182.497
+ ,1896
+ ,95.987
+ ,91.869
+ ,187.856
+ ,1897
+ ,97.175
+ ,92.845
+ ,190.020
+ ,1898
+ ,97.321
+ ,92.787
+ ,190.108
+ ,1899
+ ,98.577
+ ,94.711
+ ,193.288
+ ,1900
+ ,99.026
+ ,94.204
+ ,193.230
+ ,1901
+ ,101.851
+ ,97.217
+ ,199.068
+ ,1902
+ ,99.958
+ ,95.118
+ ,195.076
+ ,1903
+ ,97.875
+ ,93.688
+ ,191.563
+ ,1904
+ ,97.927
+ ,93.140
+ ,191.067
+ ,1905
+ ,95.149
+ ,91.516
+ ,186.665
+ ,1906
+ ,94.551
+ ,90.957
+ ,185.508
+ ,1907
+ ,93.999
+ ,90.372
+ ,184.371
+ ,1908
+ ,93.297
+ ,89.749
+ ,183.046
+ ,1909
+ ,89.901
+ ,85.813
+ ,175.714
+ ,1910
+ ,89.742
+ ,86.026
+ ,175.768
+ ,1911
+ ,87.096
+ ,83.933
+ ,171.029
+ ,1912
+ ,86.863
+ ,83.602
+ ,170.465
+ ,1913
+ ,86.718
+ ,83.384
+ ,170.102
+ ,1914
+ ,80.020
+ ,76.369
+ ,156.389
+ ,1915
+ ,63.483
+ ,60.808
+ ,124.291
+ ,1916
+ ,51.289
+ ,48.071
+ ,99.360
+ ,1917
+ ,44.071
+ ,42.604
+ ,86.675
+ ,1918
+ ,43.654
+ ,41.402
+ ,85.056
+ ,1919
+ ,66.115
+ ,62.121
+ ,128.236
+ ,1920
+ ,84.518
+ ,79.739
+ ,164.257
+ ,1921
+ ,83.395
+ ,79.006
+ ,162.401
+ ,1922
+ ,78.307
+ ,74.472
+ ,152.779
+ ,1923
+ ,80.049
+ ,75.956
+ ,156.005
+ ,1924
+ ,78.346
+ ,75.041
+ ,153.387
+ ,1925
+ ,78.317
+ ,74.873
+ ,153.190
+ ,1926
+ ,75.918
+ ,72.922
+ ,148.840
+ ,1927
+ ,73.739
+ ,70.472
+ ,144.211
+ ,1928
+ ,74.530
+ ,71.423
+ ,145.953
+ ,1929
+ ,74.179
+ ,71.363
+ ,145.542
+ ,1930
+ ,76.974
+ ,73.297
+ ,150.271
+ ,1931
+ ,75.408
+ ,72.081
+ ,147.489
+ ,1932
+ ,73.336
+ ,70.488
+ ,143.824
+ ,1933
+ ,69.210
+ ,65.544
+ ,134.754
+ ,1934
+ ,67.286
+ ,64.450
+ ,131.736
+ ,1935
+ ,64.606
+ ,61.698
+ ,126.304
+ ,1936
+ ,64.159
+ ,61.352
+ ,125.511
+ ,1937
+ ,64.423
+ ,61.072
+ ,125.495
+ ,1938
+ ,66.411
+ ,63.722
+ ,130.133
+ ,1939
+ ,64.270
+ ,61.987
+ ,126.257
+ ,1940
+ ,56.521
+ ,53.802
+ ,110.323
+ ,1941
+ ,50.599
+ ,47.818
+ ,98.417
+ ,1942
+ ,54.751
+ ,50.998
+ ,105.749
+ ,1943
+ ,62.227
+ ,58.438
+ ,120.665
+ ,1944
+ ,63.932
+ ,60.143
+ ,124.075
+ ,1945
+ ,65.391
+ ,61.854
+ ,127.245
+ ,1946
+ ,75.744
+ ,70.987
+ ,146.731
+ ,1947
+ ,74.590
+ ,70.389
+ ,144.979
+ ,1948
+ ,76.035
+ ,72.175
+ ,148.210
+ ,1949
+ ,74.427
+ ,70.243
+ ,144.670
+ ,1950
+ ,73.354
+ ,69.616
+ ,142.970
+ ,1951
+ ,73.081
+ ,69.443
+ ,142.524
+ ,1952
+ ,75.309
+ ,70.833
+ ,146.142
+ ,1953
+ ,75.463
+ ,71.059
+ ,146.522
+ ,1954
+ ,75.910
+ ,72.218
+ ,148.128
+ ,1955
+ ,76.151
+ ,72.647
+ ,148.798
+ ,1956
+ ,76.882
+ ,73.299
+ ,150.181
+ ,1957
+ ,78.632
+ ,73.756
+ ,152.388
+ ,1958
+ ,80.137
+ ,75.557
+ ,155.694
+ ,1959
+ ,82.490
+ ,78.172
+ ,160.662
+ ,1960
+ ,79.896
+ ,75.624
+ ,155.520
+ ,1961
+ ,81.303
+ ,76.959
+ ,158.262
+ ,1962
+ ,79.344
+ ,74.994
+ ,154.338
+ ,1963
+ ,81.355
+ ,76.841
+ ,158.196
+ ,1964
+ ,82.328
+ ,78.043
+ ,160.371
+ ,1965
+ ,79.669
+ ,75.187
+ ,154.856
+ ,1966
+ ,77.249
+ ,73.387
+ ,150.636
+ ,1967
+ ,75.101
+ ,70.798
+ ,145.899
+ ,1968
+ ,72.520
+ ,68.722
+ ,141.242
+ ,1969
+ ,72.438
+ ,68.396
+ ,140.834
+ ,1970
+ ,72.653
+ ,68.466
+ ,141.119
+ ,1971
+ ,71.429
+ ,67.675
+ ,139.104
+ ,1972
+ ,69.189
+ ,65.248
+ ,134.437
+ ,1973
+ ,66.451
+ ,62.974
+ ,129.425
+ ,1974
+ ,63.354
+ ,59.801
+ ,123.155
+ ,1975
+ ,61.379
+ ,57.894
+ ,119.273
+ ,1976
+ ,61.880
+ ,58.592
+ ,120.472
+ ,1977
+ ,62.274
+ ,59.249
+ ,121.523
+ ,1978
+ ,62.429
+ ,59.554
+ ,121.983
+ ,1979
+ ,63.905
+ ,59.753
+ ,123.658
+ ,1980
+ ,63.917
+ ,60.877
+ ,124.794
+ ,1981
+ ,64.295
+ ,60.532
+ ,124.827
+ ,1982
+ ,61.930
+ ,58.452
+ ,120.382
+ ,1983
+ ,60.440
+ ,56.955
+ ,117.395
+ ,1984
+ ,59.353
+ ,56.437
+ ,115.790
+ ,1985
+ ,58.695
+ ,55.588
+ ,114.283
+ ,1986
+ ,60.569
+ ,56.702
+ ,117.271
+ ,1987
+ ,60.386
+ ,57.062
+ ,117.448
+ ,1988
+ ,60.938
+ ,57.826
+ ,118.764
+ ,1989
+ ,61.795
+ ,58.755
+ ,120.550
+ ,1990
+ ,63.304
+ ,60.250
+ ,123.554
+ ,1991
+ ,64.270
+ ,61.142
+ ,125.412
+ ,1992
+ ,63.492
+ ,60.690
+ ,124.182
+ ,1993
+ ,61.333
+ ,58.495
+ ,119.828
+ ,1994
+ ,59.341
+ ,56.020
+ ,115.361
+ ,1995
+ ,58.412
+ ,55.814
+ ,114.226
+ ,1996
+ ,58.725
+ ,56.489
+ ,115.214
+ ,1997
+ ,59.277
+ ,56.587
+ ,115.864
+ ,1998
+ ,58.562
+ ,55.714
+ ,114.276
+ ,1999
+ ,57.858
+ ,55.611
+ ,113.469
+ ,2000
+ ,58.790
+ ,56.093
+ ,114.883
+ ,2001
+ ,58.243
+ ,55.929
+ ,114.172
+ ,2002
+ ,57.044
+ ,54.181
+ ,111.225
+ ,2003
+ ,57.339
+ ,54.810
+ ,112.149
+ ,2004
+ ,59.429
+ ,56.189
+ ,115.618
+ ,2005
+ ,60.575
+ ,57.427
+ ,118.002
+ ,2006
+ ,61.950
+ ,59.432
+ ,121.382
+ ,2007
+ ,61.712
+ ,58.951
+ ,120.663
+ ,2008
+ ,65.731
+ ,62.318
+ ,128.049
+ ,2009
+ ,65.197
+ ,62.100
+ ,127.297)
+ ,dim=c(4
+ ,180)
+ ,dimnames=list(c('Jaar'
+ ,'Jongens'
+ ,'Meisjes'
+ ,'Totaal')
+ ,1:180))
> y <- array(NA,dim=c(4,180),dimnames=list(c('Jaar','Jongens','Meisjes','Totaal'),1:180))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '3'
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from 'package:base':
as.Date, as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Meisjes Jaar Jongens Totaal
1 64.033 1830 67.643 131.676
2 65.679 1831 69.371 135.050
3 62.776 1832 66.294 129.070
4 67.024 1833 70.768 137.792
5 67.988 1834 71.774 139.762
6 69.529 1835 73.388 142.917
7 70.158 1836 74.040 144.198
8 69.410 1837 73.238 142.648
9 74.049 1838 78.121 152.170
10 66.197 1839 69.825 136.022
11 67.043 1840 71.099 138.142
12 67.459 1841 70.676 138.135
13 65.512 1842 69.515 135.027
14 64.665 1843 68.246 132.911
15 65.382 1844 68.594 133.976
16 66.607 1845 70.405 137.012
17 58.387 1846 61.223 119.610
18 57.564 1847 60.542 118.106
19 58.431 1848 61.952 120.383
20 65.012 1849 68.173 133.185
21 64.176 1850 67.240 131.416
22 65.509 1851 68.739 134.248
23 65.163 1852 69.234 134.397
24 62.158 1853 65.570 127.728
25 64.429 1854 67.408 131.837
26 61.325 1855 64.630 125.955
27 65.339 1856 68.848 134.187
28 69.921 1857 73.370 143.291
29 70.782 1858 74.292 145.074
30 73.287 1859 76.525 149.812
31 70.300 1860 74.368 144.668
32 71.579 1861 75.674 147.253
33 70.700 1862 74.868 145.568
34 75.740 1863 79.824 155.564
35 75.850 1864 80.022 155.872
36 76.381 1865 79.942 156.323
37 77.388 1866 80.622 158.010
38 75.519 1867 80.079 155.598
39 75.573 1868 79.212 154.785
40 76.668 1869 80.626 157.294
41 79.387 1870 83.551 162.938
42 76.876 1871 80.407 157.283
43 81.021 1872 85.053 166.074
44 82.883 1873 86.399 169.282
45 84.016 1874 88.536 172.552
46 85.047 1875 89.008 174.055
47 85.757 1876 89.652 175.409
48 84.792 1877 88.904 173.696
49 83.811 1878 87.472 171.283
50 84.691 1879 88.631 173.322
51 83.496 1880 87.221 170.717
52 85.470 1881 88.759 174.229
53 85.212 1882 90.127 175.339
54 84.802 1883 88.709 173.511
55 85.809 1884 90.030 175.839
56 85.119 1885 88.697 173.816
57 85.228 1886 88.762 173.990
58 85.302 1887 89.475 174.777
59 85.883 1888 88.936 174.819
60 86.315 1889 90.411 176.726
61 86.195 1890 90.004 176.199
62 88.227 1891 92.725 180.952
63 86.411 1892 90.252 176.663
64 89.120 1893 93.226 182.346
65 88.030 1894 92.575 180.605
66 89.372 1895 93.125 182.497
67 91.869 1896 95.987 187.856
68 92.845 1897 97.175 190.020
69 92.787 1898 97.321 190.108
70 94.711 1899 98.577 193.288
71 94.204 1900 99.026 193.230
72 97.217 1901 101.851 199.068
73 95.118 1902 99.958 195.076
74 93.688 1903 97.875 191.563
75 93.140 1904 97.927 191.067
76 91.516 1905 95.149 186.665
77 90.957 1906 94.551 185.508
78 90.372 1907 93.999 184.371
79 89.749 1908 93.297 183.046
80 85.813 1909 89.901 175.714
81 86.026 1910 89.742 175.768
82 83.933 1911 87.096 171.029
83 83.602 1912 86.863 170.465
84 83.384 1913 86.718 170.102
85 76.369 1914 80.020 156.389
86 60.808 1915 63.483 124.291
87 48.071 1916 51.289 99.360
88 42.604 1917 44.071 86.675
89 41.402 1918 43.654 85.056
90 62.121 1919 66.115 128.236
91 79.739 1920 84.518 164.257
92 79.006 1921 83.395 162.401
93 74.472 1922 78.307 152.779
94 75.956 1923 80.049 156.005
95 75.041 1924 78.346 153.387
96 74.873 1925 78.317 153.190
97 72.922 1926 75.918 148.840
98 70.472 1927 73.739 144.211
99 71.423 1928 74.530 145.953
100 71.363 1929 74.179 145.542
101 73.297 1930 76.974 150.271
102 72.081 1931 75.408 147.489
103 70.488 1932 73.336 143.824
104 65.544 1933 69.210 134.754
105 64.450 1934 67.286 131.736
106 61.698 1935 64.606 126.304
107 61.352 1936 64.159 125.511
108 61.072 1937 64.423 125.495
109 63.722 1938 66.411 130.133
110 61.987 1939 64.270 126.257
111 53.802 1940 56.521 110.323
112 47.818 1941 50.599 98.417
113 50.998 1942 54.751 105.749
114 58.438 1943 62.227 120.665
115 60.143 1944 63.932 124.075
116 61.854 1945 65.391 127.245
117 70.987 1946 75.744 146.731
118 70.389 1947 74.590 144.979
119 72.175 1948 76.035 148.210
120 70.243 1949 74.427 144.670
121 69.616 1950 73.354 142.970
122 69.443 1951 73.081 142.524
123 70.833 1952 75.309 146.142
124 71.059 1953 75.463 146.522
125 72.218 1954 75.910 148.128
126 72.647 1955 76.151 148.798
127 73.299 1956 76.882 150.181
128 73.756 1957 78.632 152.388
129 75.557 1958 80.137 155.694
130 78.172 1959 82.490 160.662
131 75.624 1960 79.896 155.520
132 76.959 1961 81.303 158.262
133 74.994 1962 79.344 154.338
134 76.841 1963 81.355 158.196
135 78.043 1964 82.328 160.371
136 75.187 1965 79.669 154.856
137 73.387 1966 77.249 150.636
138 70.798 1967 75.101 145.899
139 68.722 1968 72.520 141.242
140 68.396 1969 72.438 140.834
141 68.466 1970 72.653 141.119
142 67.675 1971 71.429 139.104
143 65.248 1972 69.189 134.437
144 62.974 1973 66.451 129.425
145 59.801 1974 63.354 123.155
146 57.894 1975 61.379 119.273
147 58.592 1976 61.880 120.472
148 59.249 1977 62.274 121.523
149 59.554 1978 62.429 121.983
150 59.753 1979 63.905 123.658
151 60.877 1980 63.917 124.794
152 60.532 1981 64.295 124.827
153 58.452 1982 61.930 120.382
154 56.955 1983 60.440 117.395
155 56.437 1984 59.353 115.790
156 55.588 1985 58.695 114.283
157 56.702 1986 60.569 117.271
158 57.062 1987 60.386 117.448
159 57.826 1988 60.938 118.764
160 58.755 1989 61.795 120.550
161 60.250 1990 63.304 123.554
162 61.142 1991 64.270 125.412
163 60.690 1992 63.492 124.182
164 58.495 1993 61.333 119.828
165 56.020 1994 59.341 115.361
166 55.814 1995 58.412 114.226
167 56.489 1996 58.725 115.214
168 56.587 1997 59.277 115.864
169 55.714 1998 58.562 114.276
170 55.611 1999 57.858 113.469
171 56.093 2000 58.790 114.883
172 55.929 2001 58.243 114.172
173 54.181 2002 57.044 111.225
174 54.810 2003 57.339 112.149
175 56.189 2004 59.429 115.618
176 57.427 2005 60.575 118.002
177 59.432 2006 61.950 121.382
178 58.951 2007 61.712 120.663
179 62.318 2008 65.731 128.049
180 62.100 2009 65.197 127.297
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Jaar Jongens Totaal
6.552e-14 -2.112e-17 -1.000e+00 1.000e+00
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-2.949e-14 -5.632e-15 -7.300e-17 7.051e-15 1.032e-13
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.552e-14 3.969e-14 1.651e+00 0.101
Jaar -2.112e-17 1.916e-17 -1.102e+00 0.272
Jongens -1.000e+00 3.899e-15 -2.564e+14 <2e-16 ***
Totaal 1.000e+00 1.983e-15 5.044e+14 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.222e-14 on 176 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: 1
F-statistic: 5.637e+31 on 3 and 176 DF, p-value: < 2.2e-16
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 0.5329247949 9.341504e-01 4.670752e-01
[2,] 0.4536078211 9.072156e-01 5.463922e-01
[3,] 0.5012218687 9.975563e-01 4.987781e-01
[4,] 0.0197693380 3.953868e-02 9.802307e-01
[5,] 0.0206245881 4.124918e-02 9.793754e-01
[6,] 0.6706314857 6.587370e-01 3.293685e-01
[7,] 0.0942642878 1.885286e-01 9.057357e-01
[8,] 0.9905746329 1.885073e-02 9.425367e-03
[9,] 0.9908427673 1.831447e-02 9.157233e-03
[10,] 0.9892455217 2.150896e-02 1.075448e-02
[11,] 0.0538510450 1.077021e-01 9.461490e-01
[12,] 0.1891468526 3.782937e-01 8.108531e-01
[13,] 0.4829650129 9.659300e-01 5.170350e-01
[14,] 0.9250569995 1.498860e-01 7.494300e-02
[15,] 0.0438319387 8.766388e-02 9.561681e-01
[16,] 0.2431188820 4.862378e-01 7.568811e-01
[17,] 0.0063048819 1.260976e-02 9.936951e-01
[18,] 0.2043972408 4.087945e-01 7.956028e-01
[19,] 0.8178078016 3.643844e-01 1.821922e-01
[20,] 0.2526700468 5.053401e-01 7.473300e-01
[21,] 0.9999475662 1.048675e-04 5.243377e-05
[22,] 0.0064183913 1.283678e-02 9.935816e-01
[23,] 0.7064885990 5.870228e-01 2.935114e-01
[24,] 0.9999852116 2.957685e-05 1.478843e-05
[25,] 0.0472130224 9.442604e-02 9.527870e-01
[26,] 0.3946592421 7.893185e-01 6.053408e-01
[27,] 0.9882685067 2.346299e-02 1.173149e-02
[28,] 0.9999880090 2.398197e-05 1.199099e-05
[29,] 0.6618130779 6.763738e-01 3.381869e-01
[30,] 0.9884157042 2.316859e-02 1.158430e-02
[31,] 0.9975441566 4.911687e-03 2.455843e-03
[32,] 0.1524419939 3.048840e-01 8.475580e-01
[33,] 0.3165445276 6.330891e-01 6.834555e-01
[34,] 0.7880264874 4.239470e-01 2.119735e-01
[35,] 0.9999094950 1.810099e-04 9.050497e-05
[36,] 0.0843845812 1.687692e-01 9.156154e-01
[37,] 0.9981420127 3.715975e-03 1.857987e-03
[38,] 0.9998209434 3.581133e-04 1.790566e-04
[39,] 0.1634781283 3.269563e-01 8.365219e-01
[40,] 0.0692030494 1.384061e-01 9.307970e-01
[41,] 0.0261056302 5.221126e-02 9.738944e-01
[42,] 0.9998020078 3.959843e-04 1.979922e-04
[43,] 0.9706527022 5.869460e-02 2.934730e-02
[44,] 0.9105080681 1.789839e-01 8.949193e-02
[45,] 0.9999998605 2.790545e-07 1.395273e-07
[46,] 0.9793404269 4.131915e-02 2.065957e-02
[47,] 0.9963874515 7.225097e-03 3.612549e-03
[48,] 0.9642038288 7.159234e-02 3.579617e-02
[49,] 0.9884939202 2.301216e-02 1.150608e-02
[50,] 1.0000000000 5.444569e-15 2.722285e-15
[51,] 0.9961716325 7.656735e-03 3.828368e-03
[52,] 0.9957836104 8.432779e-03 4.216390e-03
[53,] 1.0000000000 8.778117e-11 4.389058e-11
[54,] 0.9999157744 1.684511e-04 8.422556e-05
[55,] 0.9831887651 3.362247e-02 1.681123e-02
[56,] 0.9999160243 1.679515e-04 8.397574e-05
[57,] 1.0000000000 7.041727e-15 3.520864e-15
[58,] 0.9900563300 1.988734e-02 9.943670e-03
[59,] 0.0438854441 8.777089e-02 9.561146e-01
[60,] 1.0000000000 5.875050e-12 2.937525e-12
[61,] 0.9921498682 1.570026e-02 7.850132e-03
[62,] 0.0670717320 1.341435e-01 9.329283e-01
[63,] 0.9870928545 2.581429e-02 1.290715e-02
[64,] 1.0000000000 2.161411e-11 1.080706e-11
[65,] 1.0000000000 7.267994e-11 3.633997e-11
[66,] 0.9975293521 4.941296e-03 2.470648e-03
[67,] 1.0000000000 9.681682e-13 4.840841e-13
[68,] 0.0864066775 1.728134e-01 9.135933e-01
[69,] 0.0165075278 3.301506e-02 9.834925e-01
[70,] 0.0606110332 1.212221e-01 9.393890e-01
[71,] 0.9999433047 1.133906e-04 5.669532e-05
[72,] 0.9989660495 2.067901e-03 1.033950e-03
[73,] 1.0000000000 6.782061e-13 3.391030e-13
[74,] 0.8996916911 2.006166e-01 1.003083e-01
[75,] 0.9417693552 1.164613e-01 5.823064e-02
[76,] 1.0000000000 5.497979e-11 2.748989e-11
[77,] 0.9990890168 1.821966e-03 9.109832e-04
[78,] 0.9958849194 8.230161e-03 4.115081e-03
[79,] 0.9989252169 2.149566e-03 1.074783e-03
[80,] 0.0669294727 1.338589e-01 9.330705e-01
[81,] 0.9981500000 3.700000e-03 1.850000e-03
[82,] 1.0000000000 3.153487e-12 1.576743e-12
[83,] 0.9994272626 1.145475e-03 5.727374e-04
[84,] 0.9999999995 9.987465e-10 4.993733e-10
[85,] 0.9928925956 1.421481e-02 7.107404e-03
[86,] 1.0000000000 5.525002e-12 2.762501e-12
[87,] 0.9977682022 4.463596e-03 2.231798e-03
[88,] 0.0102451336 2.049027e-02 9.897549e-01
[89,] 0.0045279260 9.055852e-03 9.954721e-01
[90,] 0.9999999977 4.537143e-09 2.268571e-09
[91,] 0.0012795943 2.559189e-03 9.987204e-01
[92,] 0.9999999975 4.960242e-09 2.480121e-09
[93,] 0.9974907424 5.018515e-03 2.509258e-03
[94,] 0.9800537256 3.989255e-02 1.994627e-02
[95,] 0.7422671251 5.154657e-01 2.577329e-01
[96,] 0.4225967325 8.451935e-01 5.774033e-01
[97,] 0.9999999999 2.070193e-10 1.035096e-10
[98,] 0.9993516571 1.296686e-03 6.483429e-04
[99,] 0.5345391267 9.309217e-01 4.654609e-01
[100,] 0.9994505394 1.098921e-03 5.494606e-04
[101,] 0.9991396880 1.720624e-03 8.603120e-04
[102,] 0.9996681160 6.637679e-04 3.318840e-04
[103,] 0.9999999983 3.374216e-09 1.687108e-09
[104,] 0.9999999974 5.196577e-09 2.598289e-09
[105,] 0.0031337606 6.267521e-03 9.968662e-01
[106,] 0.9990632620 1.873476e-03 9.367380e-04
[107,] 0.0007101144 1.420229e-03 9.992899e-01
[108,] 0.9972745257 5.450949e-03 2.725474e-03
[109,] 0.0006457432 1.291486e-03 9.993543e-01
[110,] 0.2392240414 4.784481e-01 7.607760e-01
[111,] 0.1419495320 2.838991e-01 8.580505e-01
[112,] 0.4647770676 9.295541e-01 5.352229e-01
[113,] 0.9999999867 2.662133e-08 1.331067e-08
[114,] 0.0679480021 1.358960e-01 9.320520e-01
[115,] 0.4731503814 9.463008e-01 5.268496e-01
[116,] 0.1703838631 3.407677e-01 8.296161e-01
[117,] 0.9999969088 6.182495e-06 3.091248e-06
[118,] 0.9994113618 1.177276e-03 5.886382e-04
[119,] 0.9997365813 5.268374e-04 2.634187e-04
[120,] 0.9996047968 7.904063e-04 3.952032e-04
[121,] 0.9999987148 2.570410e-06 1.285205e-06
[122,] 0.2618875056 5.237750e-01 7.381125e-01
[123,] 0.1075411043 2.150822e-01 8.924589e-01
[124,] 0.9692255364 6.154893e-02 3.077446e-02
[125,] 0.9999999921 1.581971e-08 7.909855e-09
[126,] 0.6473383874 7.053232e-01 3.526616e-01
[127,] 0.9999990730 1.854044e-06 9.270219e-07
[128,] 0.9999996860 6.279545e-07 3.139772e-07
[129,] 0.9969021354 6.195729e-03 3.097865e-03
[130,] 0.9999998116 3.768410e-07 1.884205e-07
[131,] 0.9999990334 1.933228e-06 9.666141e-07
[132,] 0.0638540599 1.277081e-01 9.361459e-01
[133,] 0.1146912800 2.293826e-01 8.853087e-01
[134,] 0.9990536398 1.892720e-03 9.463602e-04
[135,] 0.9988674633 2.265073e-03 1.132537e-03
[136,] 0.9999983313 3.337490e-06 1.668745e-06
[137,] 0.1623314401 3.246629e-01 8.376686e-01
[138,] 0.9113255261 1.773489e-01 8.867447e-02
[139,] 0.7252950018 5.494100e-01 2.747050e-01
[140,] 0.9997668084 4.663832e-04 2.331916e-04
[141,] 0.9220646577 1.558707e-01 7.793534e-02
[142,] 0.1306058103 2.612116e-01 8.693942e-01
[143,] 0.2169556015 4.339112e-01 7.830444e-01
[144,] 0.9999992538 1.492310e-06 7.461548e-07
[145,] 0.9992712116 1.457577e-03 7.287884e-04
[146,] 0.0779019826 1.558040e-01 9.220980e-01
[147,] 0.1652439767 3.304880e-01 8.347560e-01
[148,] 0.0884320421 1.768641e-01 9.115680e-01
[149,] 0.0114154413 2.283088e-02 9.885846e-01
[150,] 0.9385564877 1.228870e-01 6.144351e-02
[151,] 0.9998760091 2.479818e-04 1.239909e-04
[152,] 0.3792684450 7.585369e-01 6.207316e-01
[153,] 0.9988888783 2.222243e-03 1.111122e-03
[154,] 0.9999295313 1.409373e-04 7.046867e-05
[155,] 0.5771843221 8.456314e-01 4.228157e-01
[156,] 0.9925826004 1.483480e-02 7.417400e-03
[157,] 0.9663163455 6.736731e-02 3.368365e-02
[158,] 0.8564126856 2.871746e-01 1.435873e-01
[159,] 0.8071533898 3.856932e-01 1.928466e-01
[160,] 0.9140051947 1.719896e-01 8.599481e-02
[161,] 0.8701345040 2.597310e-01 1.298655e-01
[162,] 0.6721806750 6.556386e-01 3.278193e-01
[163,] 0.0445028007 8.900560e-02 9.554972e-01
[164,] 0.7244729267 5.510541e-01 2.755271e-01
[165,] 0.0247315481 4.946310e-02 9.752685e-01
[166,] 0.9128625060 1.742750e-01 8.713749e-02
[167,] 0.7086232884 5.827534e-01 2.913767e-01
> postscript(file="/var/wessaorg/rcomp/tmp/1zbtf1353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/2gbgl1353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/3yac81353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/43ix61353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/5z7m71353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 180
Frequency = 1
1 2 3 4 5
1.032099e-13 -2.948963e-14 1.115780e-14 -4.518798e-15 -4.392946e-15
6 7 8 9 10
-4.703064e-15 -4.230111e-15 -4.645401e-15 1.054721e-14 8.851635e-15
11 12 13 14 15
9.583174e-15 1.005525e-14 8.959752e-15 -4.808480e-15 -3.224726e-15
16 17 18 19 20
-5.746937e-15 -8.674861e-15 4.509929e-16 -9.835829e-15 -3.892020e-15
21 22 23 24 25
-4.254230e-15 8.208461e-15 -4.097191e-15 -5.536508e-15 1.022422e-14
26 27 28 29 30
-4.256801e-15 -2.039657e-14 9.616630e-15 -1.715607e-14 -4.450941e-15
31 32 33 34 35
-1.778421e-14 1.071002e-14 -1.845145e-14 -2.343805e-15 -1.667631e-14
36 37 38 39 40
-1.615229e-14 1.230827e-14 -1.705874e-14 -2.196944e-15 -2.560119e-15
41 42 43 44 45
1.194018e-14 1.165075e-14 -1.634132e-14 -1.488887e-14 1.250402e-14
46 47 48 49 50
-1.525376e-14 1.244109e-14 1.426084e-16 1.165992e-14 -2.343755e-15
51 52 53 54 55
-1.369346e-14 -1.737837e-14 -3.213811e-15 1.249449e-14 -9.085778e-16
56 57 58 59 60
-2.341984e-15 -1.412670e-14 1.388215e-14 1.443332e-14 2.173542e-15
61 62 63 64 65
-1.158788e-14 8.424184e-15 -8.804436e-15 1.402370e-15 1.827071e-14
66 67 68 69 70
-1.293834e-14 7.368424e-15 -1.198177e-14 8.347675e-15 -6.594271e-15
71 72 73 74 75
1.058063e-14 -8.272658e-15 1.349703e-15 2.111517e-14 7.834436e-15
76 77 78 79 80
2.492779e-14 -1.004513e-14 -6.449954e-15 7.591292e-15 1.006993e-15
81 82 83 84 85
1.472446e-15 1.331646e-14 -1.719451e-15 -1.094196e-15 -1.400906e-14
86 87 88 89 90
-2.448352e-15 -4.445730e-15 2.584891e-15 8.385798e-15 5.879387e-15
91 92 93 94 95
-1.159414e-15 -1.669445e-14 -1.577581e-15 1.387148e-14 5.244601e-16
96 97 98 99 100
3.874700e-16 -5.996836e-16 -1.514178e-14 -1.043573e-15 -7.247231e-16
101 102 103 104 105
1.277921e-14 -9.490591e-16 -1.495572e-14 -8.613303e-16 1.276888e-14
106 107 108 109 110
-8.951994e-15 5.750524e-15 -1.466636e-15 -9.878535e-15 -9.880050e-15
111 112 113 114 115
9.866529e-15 -8.445646e-15 2.261580e-15 -8.900146e-15 -8.622014e-16
116 117 118 119 120
-1.079035e-16 -1.007957e-16 -1.402258e-14 -1.400677e-14 1.472154e-14
121 122 123 124 125
2.458249e-16 4.740378e-17 2.462404e-16 8.562915e-16 1.599239e-14
126 127 128 129 130
-5.054880e-16 1.015085e-16 6.359644e-16 1.655225e-14 -1.278768e-14
131 132 133 134 135
-9.700132e-15 4.330247e-15 4.247453e-15 2.036190e-15 1.473917e-15
136 137 138 139 140
1.121196e-15 5.595777e-16 4.659272e-16 5.851875e-16 4.425380e-16
141 142 143 144 145
1.085965e-15 -1.347813e-14 -1.282916e-14 -2.080938e-14 -3.267767e-16
146 147 148 149 150
-4.429932e-17 6.613682e-15 6.441132e-15 4.981526e-16 1.877366e-16
151 152 153 154 155
7.207026e-15 1.057982e-15 -5.493096e-15 -5.261306e-16 -8.126372e-15
156 157 158 159 160
-2.098819e-15 -6.456845e-16 6.906021e-15 6.999246e-15 7.633540e-15
161 162 163 164 165
2.160906e-16 -6.668879e-15 -5.593604e-15 -5.879364e-15 -5.714675e-16
166 167 168 169 170
-1.178117e-15 2.826112e-16 1.326437e-15 1.480772e-15 -4.017552e-16
171 172 173 174 175
7.829308e-15 6.995617e-15 6.123468e-15 1.637629e-15 7.407167e-15
176 177 178 179 180
7.431281e-15 4.372581e-16 8.559693e-15 -1.246340e-14 8.581765e-15
> postscript(file="/var/wessaorg/rcomp/tmp/6ibsz1353253883.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 180
Frequency = 1
lag(myerror, k = 1) myerror
0 1.032099e-13 NA
1 -2.948963e-14 1.032099e-13
2 1.115780e-14 -2.948963e-14
3 -4.518798e-15 1.115780e-14
4 -4.392946e-15 -4.518798e-15
5 -4.703064e-15 -4.392946e-15
6 -4.230111e-15 -4.703064e-15
7 -4.645401e-15 -4.230111e-15
8 1.054721e-14 -4.645401e-15
9 8.851635e-15 1.054721e-14
10 9.583174e-15 8.851635e-15
11 1.005525e-14 9.583174e-15
12 8.959752e-15 1.005525e-14
13 -4.808480e-15 8.959752e-15
14 -3.224726e-15 -4.808480e-15
15 -5.746937e-15 -3.224726e-15
16 -8.674861e-15 -5.746937e-15
17 4.509929e-16 -8.674861e-15
18 -9.835829e-15 4.509929e-16
19 -3.892020e-15 -9.835829e-15
20 -4.254230e-15 -3.892020e-15
21 8.208461e-15 -4.254230e-15
22 -4.097191e-15 8.208461e-15
23 -5.536508e-15 -4.097191e-15
24 1.022422e-14 -5.536508e-15
25 -4.256801e-15 1.022422e-14
26 -2.039657e-14 -4.256801e-15
27 9.616630e-15 -2.039657e-14
28 -1.715607e-14 9.616630e-15
29 -4.450941e-15 -1.715607e-14
30 -1.778421e-14 -4.450941e-15
31 1.071002e-14 -1.778421e-14
32 -1.845145e-14 1.071002e-14
33 -2.343805e-15 -1.845145e-14
34 -1.667631e-14 -2.343805e-15
35 -1.615229e-14 -1.667631e-14
36 1.230827e-14 -1.615229e-14
37 -1.705874e-14 1.230827e-14
38 -2.196944e-15 -1.705874e-14
39 -2.560119e-15 -2.196944e-15
40 1.194018e-14 -2.560119e-15
41 1.165075e-14 1.194018e-14
42 -1.634132e-14 1.165075e-14
43 -1.488887e-14 -1.634132e-14
44 1.250402e-14 -1.488887e-14
45 -1.525376e-14 1.250402e-14
46 1.244109e-14 -1.525376e-14
47 1.426084e-16 1.244109e-14
48 1.165992e-14 1.426084e-16
49 -2.343755e-15 1.165992e-14
50 -1.369346e-14 -2.343755e-15
51 -1.737837e-14 -1.369346e-14
52 -3.213811e-15 -1.737837e-14
53 1.249449e-14 -3.213811e-15
54 -9.085778e-16 1.249449e-14
55 -2.341984e-15 -9.085778e-16
56 -1.412670e-14 -2.341984e-15
57 1.388215e-14 -1.412670e-14
58 1.443332e-14 1.388215e-14
59 2.173542e-15 1.443332e-14
60 -1.158788e-14 2.173542e-15
61 8.424184e-15 -1.158788e-14
62 -8.804436e-15 8.424184e-15
63 1.402370e-15 -8.804436e-15
64 1.827071e-14 1.402370e-15
65 -1.293834e-14 1.827071e-14
66 7.368424e-15 -1.293834e-14
67 -1.198177e-14 7.368424e-15
68 8.347675e-15 -1.198177e-14
69 -6.594271e-15 8.347675e-15
70 1.058063e-14 -6.594271e-15
71 -8.272658e-15 1.058063e-14
72 1.349703e-15 -8.272658e-15
73 2.111517e-14 1.349703e-15
74 7.834436e-15 2.111517e-14
75 2.492779e-14 7.834436e-15
76 -1.004513e-14 2.492779e-14
77 -6.449954e-15 -1.004513e-14
78 7.591292e-15 -6.449954e-15
79 1.006993e-15 7.591292e-15
80 1.472446e-15 1.006993e-15
81 1.331646e-14 1.472446e-15
82 -1.719451e-15 1.331646e-14
83 -1.094196e-15 -1.719451e-15
84 -1.400906e-14 -1.094196e-15
85 -2.448352e-15 -1.400906e-14
86 -4.445730e-15 -2.448352e-15
87 2.584891e-15 -4.445730e-15
88 8.385798e-15 2.584891e-15
89 5.879387e-15 8.385798e-15
90 -1.159414e-15 5.879387e-15
91 -1.669445e-14 -1.159414e-15
92 -1.577581e-15 -1.669445e-14
93 1.387148e-14 -1.577581e-15
94 5.244601e-16 1.387148e-14
95 3.874700e-16 5.244601e-16
96 -5.996836e-16 3.874700e-16
97 -1.514178e-14 -5.996836e-16
98 -1.043573e-15 -1.514178e-14
99 -7.247231e-16 -1.043573e-15
100 1.277921e-14 -7.247231e-16
101 -9.490591e-16 1.277921e-14
102 -1.495572e-14 -9.490591e-16
103 -8.613303e-16 -1.495572e-14
104 1.276888e-14 -8.613303e-16
105 -8.951994e-15 1.276888e-14
106 5.750524e-15 -8.951994e-15
107 -1.466636e-15 5.750524e-15
108 -9.878535e-15 -1.466636e-15
109 -9.880050e-15 -9.878535e-15
110 9.866529e-15 -9.880050e-15
111 -8.445646e-15 9.866529e-15
112 2.261580e-15 -8.445646e-15
113 -8.900146e-15 2.261580e-15
114 -8.622014e-16 -8.900146e-15
115 -1.079035e-16 -8.622014e-16
116 -1.007957e-16 -1.079035e-16
117 -1.402258e-14 -1.007957e-16
118 -1.400677e-14 -1.402258e-14
119 1.472154e-14 -1.400677e-14
120 2.458249e-16 1.472154e-14
121 4.740378e-17 2.458249e-16
122 2.462404e-16 4.740378e-17
123 8.562915e-16 2.462404e-16
124 1.599239e-14 8.562915e-16
125 -5.054880e-16 1.599239e-14
126 1.015085e-16 -5.054880e-16
127 6.359644e-16 1.015085e-16
128 1.655225e-14 6.359644e-16
129 -1.278768e-14 1.655225e-14
130 -9.700132e-15 -1.278768e-14
131 4.330247e-15 -9.700132e-15
132 4.247453e-15 4.330247e-15
133 2.036190e-15 4.247453e-15
134 1.473917e-15 2.036190e-15
135 1.121196e-15 1.473917e-15
136 5.595777e-16 1.121196e-15
137 4.659272e-16 5.595777e-16
138 5.851875e-16 4.659272e-16
139 4.425380e-16 5.851875e-16
140 1.085965e-15 4.425380e-16
141 -1.347813e-14 1.085965e-15
142 -1.282916e-14 -1.347813e-14
143 -2.080938e-14 -1.282916e-14
144 -3.267767e-16 -2.080938e-14
145 -4.429932e-17 -3.267767e-16
146 6.613682e-15 -4.429932e-17
147 6.441132e-15 6.613682e-15
148 4.981526e-16 6.441132e-15
149 1.877366e-16 4.981526e-16
150 7.207026e-15 1.877366e-16
151 1.057982e-15 7.207026e-15
152 -5.493096e-15 1.057982e-15
153 -5.261306e-16 -5.493096e-15
154 -8.126372e-15 -5.261306e-16
155 -2.098819e-15 -8.126372e-15
156 -6.456845e-16 -2.098819e-15
157 6.906021e-15 -6.456845e-16
158 6.999246e-15 6.906021e-15
159 7.633540e-15 6.999246e-15
160 2.160906e-16 7.633540e-15
161 -6.668879e-15 2.160906e-16
162 -5.593604e-15 -6.668879e-15
163 -5.879364e-15 -5.593604e-15
164 -5.714675e-16 -5.879364e-15
165 -1.178117e-15 -5.714675e-16
166 2.826112e-16 -1.178117e-15
167 1.326437e-15 2.826112e-16
168 1.480772e-15 1.326437e-15
169 -4.017552e-16 1.480772e-15
170 7.829308e-15 -4.017552e-16
171 6.995617e-15 7.829308e-15
172 6.123468e-15 6.995617e-15
173 1.637629e-15 6.123468e-15
174 7.407167e-15 1.637629e-15
175 7.431281e-15 7.407167e-15
176 4.372581e-16 7.431281e-15
177 8.559693e-15 4.372581e-16
178 -1.246340e-14 8.559693e-15
179 8.581765e-15 -1.246340e-14
180 NA 8.581765e-15
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -2.948963e-14 1.032099e-13
[2,] 1.115780e-14 -2.948963e-14
[3,] -4.518798e-15 1.115780e-14
[4,] -4.392946e-15 -4.518798e-15
[5,] -4.703064e-15 -4.392946e-15
[6,] -4.230111e-15 -4.703064e-15
[7,] -4.645401e-15 -4.230111e-15
[8,] 1.054721e-14 -4.645401e-15
[9,] 8.851635e-15 1.054721e-14
[10,] 9.583174e-15 8.851635e-15
[11,] 1.005525e-14 9.583174e-15
[12,] 8.959752e-15 1.005525e-14
[13,] -4.808480e-15 8.959752e-15
[14,] -3.224726e-15 -4.808480e-15
[15,] -5.746937e-15 -3.224726e-15
[16,] -8.674861e-15 -5.746937e-15
[17,] 4.509929e-16 -8.674861e-15
[18,] -9.835829e-15 4.509929e-16
[19,] -3.892020e-15 -9.835829e-15
[20,] -4.254230e-15 -3.892020e-15
[21,] 8.208461e-15 -4.254230e-15
[22,] -4.097191e-15 8.208461e-15
[23,] -5.536508e-15 -4.097191e-15
[24,] 1.022422e-14 -5.536508e-15
[25,] -4.256801e-15 1.022422e-14
[26,] -2.039657e-14 -4.256801e-15
[27,] 9.616630e-15 -2.039657e-14
[28,] -1.715607e-14 9.616630e-15
[29,] -4.450941e-15 -1.715607e-14
[30,] -1.778421e-14 -4.450941e-15
[31,] 1.071002e-14 -1.778421e-14
[32,] -1.845145e-14 1.071002e-14
[33,] -2.343805e-15 -1.845145e-14
[34,] -1.667631e-14 -2.343805e-15
[35,] -1.615229e-14 -1.667631e-14
[36,] 1.230827e-14 -1.615229e-14
[37,] -1.705874e-14 1.230827e-14
[38,] -2.196944e-15 -1.705874e-14
[39,] -2.560119e-15 -2.196944e-15
[40,] 1.194018e-14 -2.560119e-15
[41,] 1.165075e-14 1.194018e-14
[42,] -1.634132e-14 1.165075e-14
[43,] -1.488887e-14 -1.634132e-14
[44,] 1.250402e-14 -1.488887e-14
[45,] -1.525376e-14 1.250402e-14
[46,] 1.244109e-14 -1.525376e-14
[47,] 1.426084e-16 1.244109e-14
[48,] 1.165992e-14 1.426084e-16
[49,] -2.343755e-15 1.165992e-14
[50,] -1.369346e-14 -2.343755e-15
[51,] -1.737837e-14 -1.369346e-14
[52,] -3.213811e-15 -1.737837e-14
[53,] 1.249449e-14 -3.213811e-15
[54,] -9.085778e-16 1.249449e-14
[55,] -2.341984e-15 -9.085778e-16
[56,] -1.412670e-14 -2.341984e-15
[57,] 1.388215e-14 -1.412670e-14
[58,] 1.443332e-14 1.388215e-14
[59,] 2.173542e-15 1.443332e-14
[60,] -1.158788e-14 2.173542e-15
[61,] 8.424184e-15 -1.158788e-14
[62,] -8.804436e-15 8.424184e-15
[63,] 1.402370e-15 -8.804436e-15
[64,] 1.827071e-14 1.402370e-15
[65,] -1.293834e-14 1.827071e-14
[66,] 7.368424e-15 -1.293834e-14
[67,] -1.198177e-14 7.368424e-15
[68,] 8.347675e-15 -1.198177e-14
[69,] -6.594271e-15 8.347675e-15
[70,] 1.058063e-14 -6.594271e-15
[71,] -8.272658e-15 1.058063e-14
[72,] 1.349703e-15 -8.272658e-15
[73,] 2.111517e-14 1.349703e-15
[74,] 7.834436e-15 2.111517e-14
[75,] 2.492779e-14 7.834436e-15
[76,] -1.004513e-14 2.492779e-14
[77,] -6.449954e-15 -1.004513e-14
[78,] 7.591292e-15 -6.449954e-15
[79,] 1.006993e-15 7.591292e-15
[80,] 1.472446e-15 1.006993e-15
[81,] 1.331646e-14 1.472446e-15
[82,] -1.719451e-15 1.331646e-14
[83,] -1.094196e-15 -1.719451e-15
[84,] -1.400906e-14 -1.094196e-15
[85,] -2.448352e-15 -1.400906e-14
[86,] -4.445730e-15 -2.448352e-15
[87,] 2.584891e-15 -4.445730e-15
[88,] 8.385798e-15 2.584891e-15
[89,] 5.879387e-15 8.385798e-15
[90,] -1.159414e-15 5.879387e-15
[91,] -1.669445e-14 -1.159414e-15
[92,] -1.577581e-15 -1.669445e-14
[93,] 1.387148e-14 -1.577581e-15
[94,] 5.244601e-16 1.387148e-14
[95,] 3.874700e-16 5.244601e-16
[96,] -5.996836e-16 3.874700e-16
[97,] -1.514178e-14 -5.996836e-16
[98,] -1.043573e-15 -1.514178e-14
[99,] -7.247231e-16 -1.043573e-15
[100,] 1.277921e-14 -7.247231e-16
[101,] -9.490591e-16 1.277921e-14
[102,] -1.495572e-14 -9.490591e-16
[103,] -8.613303e-16 -1.495572e-14
[104,] 1.276888e-14 -8.613303e-16
[105,] -8.951994e-15 1.276888e-14
[106,] 5.750524e-15 -8.951994e-15
[107,] -1.466636e-15 5.750524e-15
[108,] -9.878535e-15 -1.466636e-15
[109,] -9.880050e-15 -9.878535e-15
[110,] 9.866529e-15 -9.880050e-15
[111,] -8.445646e-15 9.866529e-15
[112,] 2.261580e-15 -8.445646e-15
[113,] -8.900146e-15 2.261580e-15
[114,] -8.622014e-16 -8.900146e-15
[115,] -1.079035e-16 -8.622014e-16
[116,] -1.007957e-16 -1.079035e-16
[117,] -1.402258e-14 -1.007957e-16
[118,] -1.400677e-14 -1.402258e-14
[119,] 1.472154e-14 -1.400677e-14
[120,] 2.458249e-16 1.472154e-14
[121,] 4.740378e-17 2.458249e-16
[122,] 2.462404e-16 4.740378e-17
[123,] 8.562915e-16 2.462404e-16
[124,] 1.599239e-14 8.562915e-16
[125,] -5.054880e-16 1.599239e-14
[126,] 1.015085e-16 -5.054880e-16
[127,] 6.359644e-16 1.015085e-16
[128,] 1.655225e-14 6.359644e-16
[129,] -1.278768e-14 1.655225e-14
[130,] -9.700132e-15 -1.278768e-14
[131,] 4.330247e-15 -9.700132e-15
[132,] 4.247453e-15 4.330247e-15
[133,] 2.036190e-15 4.247453e-15
[134,] 1.473917e-15 2.036190e-15
[135,] 1.121196e-15 1.473917e-15
[136,] 5.595777e-16 1.121196e-15
[137,] 4.659272e-16 5.595777e-16
[138,] 5.851875e-16 4.659272e-16
[139,] 4.425380e-16 5.851875e-16
[140,] 1.085965e-15 4.425380e-16
[141,] -1.347813e-14 1.085965e-15
[142,] -1.282916e-14 -1.347813e-14
[143,] -2.080938e-14 -1.282916e-14
[144,] -3.267767e-16 -2.080938e-14
[145,] -4.429932e-17 -3.267767e-16
[146,] 6.613682e-15 -4.429932e-17
[147,] 6.441132e-15 6.613682e-15
[148,] 4.981526e-16 6.441132e-15
[149,] 1.877366e-16 4.981526e-16
[150,] 7.207026e-15 1.877366e-16
[151,] 1.057982e-15 7.207026e-15
[152,] -5.493096e-15 1.057982e-15
[153,] -5.261306e-16 -5.493096e-15
[154,] -8.126372e-15 -5.261306e-16
[155,] -2.098819e-15 -8.126372e-15
[156,] -6.456845e-16 -2.098819e-15
[157,] 6.906021e-15 -6.456845e-16
[158,] 6.999246e-15 6.906021e-15
[159,] 7.633540e-15 6.999246e-15
[160,] 2.160906e-16 7.633540e-15
[161,] -6.668879e-15 2.160906e-16
[162,] -5.593604e-15 -6.668879e-15
[163,] -5.879364e-15 -5.593604e-15
[164,] -5.714675e-16 -5.879364e-15
[165,] -1.178117e-15 -5.714675e-16
[166,] 2.826112e-16 -1.178117e-15
[167,] 1.326437e-15 2.826112e-16
[168,] 1.480772e-15 1.326437e-15
[169,] -4.017552e-16 1.480772e-15
[170,] 7.829308e-15 -4.017552e-16
[171,] 6.995617e-15 7.829308e-15
[172,] 6.123468e-15 6.995617e-15
[173,] 1.637629e-15 6.123468e-15
[174,] 7.407167e-15 1.637629e-15
[175,] 7.431281e-15 7.407167e-15
[176,] 4.372581e-16 7.431281e-15
[177,] 8.559693e-15 4.372581e-16
[178,] -1.246340e-14 8.559693e-15
[179,] 8.581765e-15 -1.246340e-14
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -2.948963e-14 1.032099e-13
2 1.115780e-14 -2.948963e-14
3 -4.518798e-15 1.115780e-14
4 -4.392946e-15 -4.518798e-15
5 -4.703064e-15 -4.392946e-15
6 -4.230111e-15 -4.703064e-15
7 -4.645401e-15 -4.230111e-15
8 1.054721e-14 -4.645401e-15
9 8.851635e-15 1.054721e-14
10 9.583174e-15 8.851635e-15
11 1.005525e-14 9.583174e-15
12 8.959752e-15 1.005525e-14
13 -4.808480e-15 8.959752e-15
14 -3.224726e-15 -4.808480e-15
15 -5.746937e-15 -3.224726e-15
16 -8.674861e-15 -5.746937e-15
17 4.509929e-16 -8.674861e-15
18 -9.835829e-15 4.509929e-16
19 -3.892020e-15 -9.835829e-15
20 -4.254230e-15 -3.892020e-15
21 8.208461e-15 -4.254230e-15
22 -4.097191e-15 8.208461e-15
23 -5.536508e-15 -4.097191e-15
24 1.022422e-14 -5.536508e-15
25 -4.256801e-15 1.022422e-14
26 -2.039657e-14 -4.256801e-15
27 9.616630e-15 -2.039657e-14
28 -1.715607e-14 9.616630e-15
29 -4.450941e-15 -1.715607e-14
30 -1.778421e-14 -4.450941e-15
31 1.071002e-14 -1.778421e-14
32 -1.845145e-14 1.071002e-14
33 -2.343805e-15 -1.845145e-14
34 -1.667631e-14 -2.343805e-15
35 -1.615229e-14 -1.667631e-14
36 1.230827e-14 -1.615229e-14
37 -1.705874e-14 1.230827e-14
38 -2.196944e-15 -1.705874e-14
39 -2.560119e-15 -2.196944e-15
40 1.194018e-14 -2.560119e-15
41 1.165075e-14 1.194018e-14
42 -1.634132e-14 1.165075e-14
43 -1.488887e-14 -1.634132e-14
44 1.250402e-14 -1.488887e-14
45 -1.525376e-14 1.250402e-14
46 1.244109e-14 -1.525376e-14
47 1.426084e-16 1.244109e-14
48 1.165992e-14 1.426084e-16
49 -2.343755e-15 1.165992e-14
50 -1.369346e-14 -2.343755e-15
51 -1.737837e-14 -1.369346e-14
52 -3.213811e-15 -1.737837e-14
53 1.249449e-14 -3.213811e-15
54 -9.085778e-16 1.249449e-14
55 -2.341984e-15 -9.085778e-16
56 -1.412670e-14 -2.341984e-15
57 1.388215e-14 -1.412670e-14
58 1.443332e-14 1.388215e-14
59 2.173542e-15 1.443332e-14
60 -1.158788e-14 2.173542e-15
61 8.424184e-15 -1.158788e-14
62 -8.804436e-15 8.424184e-15
63 1.402370e-15 -8.804436e-15
64 1.827071e-14 1.402370e-15
65 -1.293834e-14 1.827071e-14
66 7.368424e-15 -1.293834e-14
67 -1.198177e-14 7.368424e-15
68 8.347675e-15 -1.198177e-14
69 -6.594271e-15 8.347675e-15
70 1.058063e-14 -6.594271e-15
71 -8.272658e-15 1.058063e-14
72 1.349703e-15 -8.272658e-15
73 2.111517e-14 1.349703e-15
74 7.834436e-15 2.111517e-14
75 2.492779e-14 7.834436e-15
76 -1.004513e-14 2.492779e-14
77 -6.449954e-15 -1.004513e-14
78 7.591292e-15 -6.449954e-15
79 1.006993e-15 7.591292e-15
80 1.472446e-15 1.006993e-15
81 1.331646e-14 1.472446e-15
82 -1.719451e-15 1.331646e-14
83 -1.094196e-15 -1.719451e-15
84 -1.400906e-14 -1.094196e-15
85 -2.448352e-15 -1.400906e-14
86 -4.445730e-15 -2.448352e-15
87 2.584891e-15 -4.445730e-15
88 8.385798e-15 2.584891e-15
89 5.879387e-15 8.385798e-15
90 -1.159414e-15 5.879387e-15
91 -1.669445e-14 -1.159414e-15
92 -1.577581e-15 -1.669445e-14
93 1.387148e-14 -1.577581e-15
94 5.244601e-16 1.387148e-14
95 3.874700e-16 5.244601e-16
96 -5.996836e-16 3.874700e-16
97 -1.514178e-14 -5.996836e-16
98 -1.043573e-15 -1.514178e-14
99 -7.247231e-16 -1.043573e-15
100 1.277921e-14 -7.247231e-16
101 -9.490591e-16 1.277921e-14
102 -1.495572e-14 -9.490591e-16
103 -8.613303e-16 -1.495572e-14
104 1.276888e-14 -8.613303e-16
105 -8.951994e-15 1.276888e-14
106 5.750524e-15 -8.951994e-15
107 -1.466636e-15 5.750524e-15
108 -9.878535e-15 -1.466636e-15
109 -9.880050e-15 -9.878535e-15
110 9.866529e-15 -9.880050e-15
111 -8.445646e-15 9.866529e-15
112 2.261580e-15 -8.445646e-15
113 -8.900146e-15 2.261580e-15
114 -8.622014e-16 -8.900146e-15
115 -1.079035e-16 -8.622014e-16
116 -1.007957e-16 -1.079035e-16
117 -1.402258e-14 -1.007957e-16
118 -1.400677e-14 -1.402258e-14
119 1.472154e-14 -1.400677e-14
120 2.458249e-16 1.472154e-14
121 4.740378e-17 2.458249e-16
122 2.462404e-16 4.740378e-17
123 8.562915e-16 2.462404e-16
124 1.599239e-14 8.562915e-16
125 -5.054880e-16 1.599239e-14
126 1.015085e-16 -5.054880e-16
127 6.359644e-16 1.015085e-16
128 1.655225e-14 6.359644e-16
129 -1.278768e-14 1.655225e-14
130 -9.700132e-15 -1.278768e-14
131 4.330247e-15 -9.700132e-15
132 4.247453e-15 4.330247e-15
133 2.036190e-15 4.247453e-15
134 1.473917e-15 2.036190e-15
135 1.121196e-15 1.473917e-15
136 5.595777e-16 1.121196e-15
137 4.659272e-16 5.595777e-16
138 5.851875e-16 4.659272e-16
139 4.425380e-16 5.851875e-16
140 1.085965e-15 4.425380e-16
141 -1.347813e-14 1.085965e-15
142 -1.282916e-14 -1.347813e-14
143 -2.080938e-14 -1.282916e-14
144 -3.267767e-16 -2.080938e-14
145 -4.429932e-17 -3.267767e-16
146 6.613682e-15 -4.429932e-17
147 6.441132e-15 6.613682e-15
148 4.981526e-16 6.441132e-15
149 1.877366e-16 4.981526e-16
150 7.207026e-15 1.877366e-16
151 1.057982e-15 7.207026e-15
152 -5.493096e-15 1.057982e-15
153 -5.261306e-16 -5.493096e-15
154 -8.126372e-15 -5.261306e-16
155 -2.098819e-15 -8.126372e-15
156 -6.456845e-16 -2.098819e-15
157 6.906021e-15 -6.456845e-16
158 6.999246e-15 6.906021e-15
159 7.633540e-15 6.999246e-15
160 2.160906e-16 7.633540e-15
161 -6.668879e-15 2.160906e-16
162 -5.593604e-15 -6.668879e-15
163 -5.879364e-15 -5.593604e-15
164 -5.714675e-16 -5.879364e-15
165 -1.178117e-15 -5.714675e-16
166 2.826112e-16 -1.178117e-15
167 1.326437e-15 2.826112e-16
168 1.480772e-15 1.326437e-15
169 -4.017552e-16 1.480772e-15
170 7.829308e-15 -4.017552e-16
171 6.995617e-15 7.829308e-15
172 6.123468e-15 6.995617e-15
173 1.637629e-15 6.123468e-15
174 7.407167e-15 1.637629e-15
175 7.431281e-15 7.407167e-15
176 4.372581e-16 7.431281e-15
177 8.559693e-15 4.372581e-16
178 -1.246340e-14 8.559693e-15
179 8.581765e-15 -1.246340e-14
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/7mgrb1353253884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/8b3rd1353253884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/wessaorg/rcomp/tmp/9c05p1353253884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/wessaorg/rcomp/tmp/10vzaa1353253884.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/11aqep1353253884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/12uy181353253884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/13ntms1353253884.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/14u91o1353253884.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/15emms1353253884.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/wessaorg/rcomp/tmp/16izqf1353253884.tab")
+ }
>
> try(system("convert tmp/1zbtf1353253883.ps tmp/1zbtf1353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gbgl1353253883.ps tmp/2gbgl1353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/3yac81353253883.ps tmp/3yac81353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/43ix61353253883.ps tmp/43ix61353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/5z7m71353253883.ps tmp/5z7m71353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/6ibsz1353253883.ps tmp/6ibsz1353253883.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mgrb1353253884.ps tmp/7mgrb1353253884.png",intern=TRUE))
character(0)
> try(system("convert tmp/8b3rd1353253884.ps tmp/8b3rd1353253884.png",intern=TRUE))
character(0)
> try(system("convert tmp/9c05p1353253884.ps tmp/9c05p1353253884.png",intern=TRUE))
character(0)
> try(system("convert tmp/10vzaa1353253884.ps tmp/10vzaa1353253884.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
7.929 0.837 8.776